Hassanieh, who was a grad student in CSAIL Professor Dina Katabi’s lab, demonstrated the many applications of his algorithms in building systems to solve problems in areas like wireless networks, mobile systems, computer graphics, medical imaging, biochemistry and digital circuits.

His dissertation showed a new way to reduce the size of computation needed for data processing, making programs in many areas of computing more efficient. Before his work, the Fast Fourier Transform (FFT) was considered the most efficient algorithm in this realm, but with the influx of Big Data, the FFT can no longer keep up. SFT can be processed at 10 to 100 times faster than before, which largely increases the power of devices and networks.

Hassanieh is an assistant professor in the computer science and electrical and computer engineering departments at the University of Illinois at Urbana-Champaign. He received his MS and PhD at MIT and his BS in Engineering from the American University of Beirut.

ACM will formally recognize Hassanieh at its annual awards banquet in San Francisco in June.